Prediction of scour depth at piers with debris accumulation effects using linear genetic programming

Abstract

Exact evaluation of scour depth around piers under debris accumulation is crucial for the safe design of pier structures. Experimental studies on scouring around pier bridges with debris accumulation have been conducted to estimate the maximum scour depth using various empirical relationships. However, due to the oversimplification of a complex process, the proposed relationships have not always been able to accurately predict the pier scour depth. This research proposes linear genetic programming (LGP) approach as an extension of the genetic programming to predict the scour depth around bridge piers. Among the artificial intelligence techniques, LGP and locally weighted linear regression (LWLR) models have not been used to predict the scour depth at bridge piers. Literature experimental data were collected and used to develop the models. The performance of the LGP method was compared with gene-expression programming, LWLR, multilinear regression and empirical equations using rigorous statistical criteria. The correlation coefficient (R) and the root mean squared error (RMSE) were (R?=?0.962, RMSE =0.31) and (R?=?0.885, RMSE =0.542) for the LGP and LWLR, respectively. The results demonstrated the superiority of the LGP method for increasing the accuracy of the predicted scour depth in comparison with the other models.     

Development of a new wavelet-based hybrid model to forecast multi-scalar SPEI drought index (case study: Zanjan city,Iran)

Theoretical and Applied Climatology - Drought forecasting plays a vital role in managing drought and reducing its effects on agricultural systems and water resources. In the present study, three...     

Crack patterns in clayey soils: Experiments and modeling

The paper presents an experimental and numerical study to investigate the behavior of desiccated clayey soils. The performed tests permit to evaluate the crack pattern as well as the tensile strength as a function of suction. A new model that relates the porosity evolution to the suction and to the tensile strength was developed and implemented in the finite element program CODE_BRIGHT. The proposed model captured the initiation and propagation of cracks in a thin layer of desiccated clay and predicted crack patterns in terms of the Minkowski densities (i.e. average crack length and crack intensity factor). The effect of the heterogeneity of the tested specimens, modeled by random clusters, was also quantified. Copyright © 2011 John Wiley & Sons, Ltd.